Desearch MCP Server
OfficialDesearch MCP server gives AI agents AI-powered search, X (Twitter) data, and page extraction through a Desearch API key (local stdio or hosted Streamable HTTP).
AI Search (
ai-search): runs AI web/Twitter search with links and optional summary, picking sources likeweb,twitter,arxiv,wikipedia,youtube,hackernews,reddit, with date ranges, domain include/exclude filters, model choice (NOVA/ORBIT), and links-only vs. summarized results.X Search (
x-search): searches tweets with filters for user, date range, language, verification, media type, and minimum retweets/replies/likes; sort stays Top.Web Search (
web-search): SERP-style ranked titles, links, and snippets, with a pagination offset.Link search (
web-links-search,x-links-search): returns web links or X post links matching a prompt (10–200 results).X post retrieval (
x-posts-by-urls,x-post-by-id,x-posts-by-user): fetches full posts by URL list, single post ID, or a specific user (with optional keyword query).X engagement and timelines (
x-post-replies,x-post-retweeters,x-user-posts,x-user-replies): pulls replies, retweeters, a user's timeline, and a user's posts/replies, with cursor pagination where supported.X Trends (
x-trends): lists trending topics for a location by WOEID (30–100 trends).Page extraction (
extract, and legacyweb-crawl): reads a public URL as plain text or HTML, optionally rendering JavaScript and waiting a set time.Flexible deployment: run locally over stdio with
DESEARCH_API_KEY, or connect to the hosted Streamable HTTP endpoint athttps://mcp.desearch.ai/mcpsending the key per request viax-api-keyorAuthorization: Bearer.
Provides link search over arXiv through the web-links-search tool, enabling retrieval of relevant arXiv paper links for a given prompt.
Provides link search over Reddit through the web-links-search tool, enabling retrieval of relevant Reddit links for a given prompt.
Provides link search over Wikipedia through the web-links-search tool, enabling retrieval of relevant Wikipedia links for a given prompt.
Provides link search over YouTube through the web-links-search tool, enabling retrieval of relevant YouTube links for a given prompt.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Desearch MCP Serversearch for latest AI developments on X"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Desearch MCP Server
AI search, X search and web search for AI agents, plus page extraction and X data tools. Bring your own Desearch API key.
Tools
The Desearch MCP server includes the following tools:
AI Search (
ai-search): Performs AI Twitter and web searches with relevant links and summary.toolsuses short source ids (web,twitter,arxiv,wikipedia,youtube,hackernews,reddit). Older labels such asWeb Searchare still accepted and sent to the API as the short id. Default is["web", "twitter"].X Search (
x-search): Tweet search on X. Arguments:query(required),count(optional, default 20). Sort stays Top. Optional filters:user,start_date,end_date(YYYY-MM-DD),lang,verified,blue_verified,is_quote,is_video,is_image,min_retweets,min_replies,min_likes.Web Search (
web-search): SERP-style web search. Arguments:query(required),start(optional pagination offset).Web Links Search (
web-links-search): Web link search. Arguments:prompt(required),tools(optional, onlyweb, default["web"];Web Searchis accepted and rewritten toweb),count(optional, 10–200). The links/web API rejects other sources, so they are not in the enum.Extract (
extract): Read a public URL as text or HTML. Preferred over crawl. Arguments:url(required),format(optional,htmlortext),js(optional),wait(optional milliseconds).Web Crawl (
web-crawl): Same arguments asextract, on the legacy/web/crawlroute. The SDK markswebCrawldeprecated in favor ofextract; this tool stays so that route remains reachable. Preferextractfor new integrations.X Links Search (
x-links-search): AI search for X post links. Arguments:prompt(required),count(optional, 10–200).X Posts By URLs (
x-posts-by-urls): Full posts for a list of URLs. Argument:urls(required).X Post By ID (
x-post-by-id): One post by ID. Argument:id(required).X Posts By User (
x-posts-by-user): Posts by a user. Arguments:user(required),query(optional),count(optional, 1–100).X Post Retweeters (
x-post-retweeters): Users who retweeted a post. Arguments:id(required),cursor(optional).X User Posts (
x-user-posts): A user's timeline. Arguments:username(required),cursor(optional).X User Replies (
x-user-replies): Posts and replies by a user. Arguments:user(required),count(optional, 1–100),query(optional).X Post Replies (
x-post-replies): Replies to a post. Arguments:post_id(required),count(optional, 1–100),query(optional).X Trends (
x-trends): Trending topics for a location. Arguments:woeid(required),count(optional, 30–100).
The full SDK method → endpoint → MCP tool map is in docs/API_MCP_PARITY.md. Every public desearch-js 1.5 method is a tool. latestTweets was removed from the SDK (GET /twitter/latest in 1.0.1) and is not exposed.
Related MCP server: grok-mcp-server
Prerequisites 📋
Node.js (v20.18.1 or higher; Node 22 is supported. Node 18 is not.)
Claude Desktop installed
Installation 🛠️
NPM Installation
The package name is desearch-mcp-server. The current version is on npm. See CHANGELOG.md for release notes. The stdio entry is the desearch-mcp-server bin (build/index.js), which requires DESEARCH_API_KEY.
npm install -g desearch-mcp-serverOr run it without a global install:
npx -y desearch-mcp-serverCursor or Claude can start that bin directly:
{
"mcpServers": {
"desearch": {
"command": "npx",
"args": ["-y", "desearch-mcp-server"],
"env": {
"DESEARCH_API_KEY": "your-api-key"
}
}
}
}command: "desearch-mcp-server" (no args) is the same entry after the global install above.
Gemini CLI
Install the extension from this repository. Gemini CLI asks for your Desearch API key (stored as a sensitive setting) and connects to the hosted server https://mcp.desearch.ai/mcp:
gemini extensions install https://github.com/Desearch-ai/mcp-desearchTo change the key later, run gemini extensions config desearch. AI agents such as Cline can follow llms-install.md to set up the server.
Using Smithery
To install the Desearch MCP server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install desearch/desearch --client claudeOr for Cursor IDE:
npx -y @smithery/cli install desearch/desearch --client cursorWindsurf
Windsurf's Cascade agent reads MCP servers from mcp_config.json under the mcpServers key. Open it from the Cascade panel: click the ... (Actions) menu, then Open MCP config file. Windsurf builds use ~/.codeium/windsurf/mcp_config.json (on Windows, %USERPROFILE%\.codeium\windsurf\mcp_config.json). Newer builds may open ~/.config/devin/mcp_config.json instead (Windows: %APPDATA%\devin\mcp_config.json); edit whichever file that action opens.
Hosted server (no local install). Remote servers use serverUrl with headers:
{
"mcpServers": {
"desearch": {
"serverUrl": "https://mcp.desearch.ai/mcp",
"headers": {
"x-api-key": "your-api-key"
}
}
}
}To keep the key out of the file, Windsurf can interpolate an environment variable: "x-api-key": "${env:DESEARCH_API_KEY}".
Local stdio alternative:
{
"mcpServers": {
"desearch": {
"command": "npx",
"args": ["-y", "desearch-mcp-server"],
"env": {
"DESEARCH_API_KEY": "your-api-key"
}
}
}
}Save the file, then refresh the MCP servers list in Cascade.
Zed
Zed calls MCP servers context servers. Open your settings file with the zed: open settings file action (or use Settings → AI → MCP Servers → Add Server) and add a context_servers entry.
Hosted server:
{
"context_servers": {
"desearch": {
"url": "https://mcp.desearch.ai/mcp",
"headers": {
"x-api-key": "your-api-key"
}
}
}
}Local stdio alternative:
{
"context_servers": {
"desearch": {
"command": "npx",
"args": ["-y", "desearch-mcp-server"],
"env": {
"DESEARCH_API_KEY": "your-api-key"
}
}
}
}The server is ready when the dot next to desearch in Settings → AI → MCP Servers turns green ("Server is active").
Configuration ⚙️
1. Configure Cursor IDE to run the Desearch MCP server
Open Cursor IDE, access command palette Cmd+Shift+P or Ctrl+Shift+P, and search for Open MCP Settings. Click on Add new global MCP server to open the mcp.json file.
2. Add the Desearch server configuration:
{
"mcpServers": {
"desearch": {
"command": "desearch-mcp-server",
"env": {
"DESEARCH_API_KEY": "your-api-key"
}
}
}
}Replace your-api-key with your actual Desearch API key from console.desearch.ai/api-keys.
3. Restart Cursor IDE
For the changes to take effect:
Completely quit Cursor IDE
Start Cursor IDE again
1. Configure Claude Desktop to run the Desearch MCP server
Open the Claude Desktop app and enable Developer Mode from the top-left menu bar.
Once enabled, open Settings (also from the top-left menu bar) and navigate to the Developer Option, where you'll find the Edit Config button. Clicking it will open the claude_desktop_config.json file, allowing you to make the necessary edits.
OR (if you want to open claude_desktop_config.json from terminal)
For macOS:
Open your Claude Desktop config:
code ~/Library/Application\ Support/Claude/claude_desktop_config.jsonFor Windows:
Open your Claude Desktop configuration:
code %APPDATA%\Claude\claude_desktop_config.json2. Add the Desearch server configuration:
{
"mcpServers": {
"desearch": {
"command": "desearch-mcp-server",
"env": {
"DESEARCH_API_KEY": "your-api-key"
}
}
}
}Replace your-api-key with your actual Desearch API key from console.desearch.ai/api-keys.
3. Restart Claude Desktop
For the changes to take effect:
Completely quit Claude Desktop
Start Claude Desktop again
You can verify the server by checking status in Settings > Developer > desearch
Remote Streamable HTTP
The same server can run over MCP Streamable HTTP for a remote client. Local stdio (desearch-mcp-server, Smithery) is unchanged and still reads DESEARCH_API_KEY from the environment.
Remote requests do not use that environment variable. Discovery does not need a key: initialize, notifications/initialized, ping, tools/list, prompts/list, resources/list, and resources/templates/list return 200 so a marketplace scanner can read the tool list. tools/call and every other method still require the caller's own Desearch API key, the same key from console.desearch.ai/api-keys:
Authorization: Bearer <DESEARCH_API_KEY>(preferred)x-api-key: <DESEARCH_API_KEY>
A bare Authorization: <DESEARCH_API_KEY> value is also accepted. The key is not read from the query string. There is no shared server secret and no WWW-Authenticate challenge: the hosted process forwards the per-request key to the Desearch API only when a call needs it.
The MCP endpoint is POST /mcp. Responses are JSON (stateless Streamable HTTP). GET and DELETE on /mcp return 405 because the server does not keep a session or push server-to-client messages. GET /, GET /health, and GET /api/health are unauthenticated health checks.
Hosted endpoint
The public Streamable HTTP endpoint is https://mcp.desearch.ai/mcp. Listing the tools does not need a key. Send your Desearch API key on each tools/call in the x-api-key header. Authorization: Bearer <key> is also accepted. Use the key from console.desearch.ai/api-keys. The server does not read a key from the query string. Remote requests do not use a process-level DESEARCH_API_KEY.
Cursor, or any remote MCP client:
{
"mcpServers": {
"desearch": {
"url": "https://mcp.desearch.ai/mcp",
"headers": {
"x-api-key": "your-api-key"
}
}
}
}Use with Claude (custom connector)
Desearch is not in the Claude Connectors Directory yet. You can add the hosted server as a custom connector with your Desearch API key.
Sources: Custom remote MCP connectors and connector authentication. Request-header authentication is a beta feature in Claude.
Claude.ai / Claude Desktop (organization admin)
Open Organization settings > Connectors.
Select Add, then Custom. If asked for the connector type, choose Web.
Server URL:
https://mcp.desearch.ai/mcpSign-in option: No sign-in.
Under Request headers, add
x-api-keywith your Desearch API key as the value.Select Add.
The header value is stored once and shared by everyone in the organization who uses the connector.
Claude Code
claude mcp add --transport http desearch https://mcp.desearch.ai/mcp \
--header "x-api-key: YOUR_DESEARCH_API_KEY"Run locally
npm install
npm run build
npm run start:httpThis listens on 0.0.0.0:3000 (PORT and HOST override that). MCP_TRANSPORT=http is the same as --http.
curl -sS http://127.0.0.1:3000/mcp \
-H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-H 'Authorization: Bearer your-api-key' \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"smoke","version":"0.0.1"}}}'Cursor (or any remote MCP client):
{
"mcpServers": {
"desearch": {
"url": "http://127.0.0.1:3000/mcp",
"headers": {
"Authorization": "Bearer your-api-key"
}
}
}
}The image default is stdio MCP (node build/index.js). Registries such as Glama start the container and speak MCP on stdin/stdout, so the image does not pass --http unless you override it. Stdio requires DESEARCH_API_KEY. Smithery does not use this image command; smithery.yaml starts node build/index.js and injects DESEARCH_API_KEY itself.
Streamable HTTP is an override. Replace the command with --http, or set MCP_TRANSPORT=http and keep the default command. The image still exposes port 3000 for that mode.
docker build -t desearch-mcp .
# stdio (image default)
docker run --rm -e DESEARCH_API_KEY=your-api-key -i desearch-mcp
# Streamable HTTP
docker run --rm -p 3000:3000 desearch-mcp node build/index.js --http
# same HTTP mode via env, without replacing the command
docker run --rm -e MCP_TRANSPORT=http -p 3000:3000 desearch-mcpDeploy on Vercel
Vercel fits this server because the handler is stateless and answers each JSON-RPC call in one response. vercel.json builds the project, serves POST /mcp, and sets the function duration to 60 seconds. Hobby plans cap function duration lower than that, so AI Search tool calls need a plan that allows at least 60 seconds. initialize and tools/list are short either way.
No server-side Desearch API key is required in the Vercel project. After deploy, the endpoint is:
https://<project>.vercel.app/mcp
https://mcp.desearch.ai/mcp is the public hostname. This repo does not create DNS records. Clients send x-api-key, or Authorization: Bearer <key>.
The same node build/index.js --http process is the fallback if you would rather run a long-lived Node host instead of Vercel. The Docker image defaults to stdio; pass --http or set MCP_TRANSPORT=http to serve Streamable HTTP from it.
Troubleshooting 🔧
Common Issues
Server Not Found
Check Claude or Cursor Desktop configuration syntax
Ensure Node.js is installed
API Key Issues
Confirm your
DESEARCH_API_KEYis validCheck the
DESEARCH_API_KEYis correctly set in the Cursor or Claude Desktop configVerify that there are no spaces around the API key
For the remote HTTP server, send
Authorization: Bearer <key>orx-api-key. A hostedDESEARCH_API_KEYenvironment variable is not used for those requests.
Connection Issues
Restart Claude Desktop or Cursor IDE completely
Check Claude Desktop logs:
# macOS tail -n 50 -f ~/Library/Logs/Claude/mcp*.log # Windows type "%APPDATA%\Claude\logs\mcp*.log"
Available Tools
15 toolsai-searchAI SearchCRead-onlyInspect
AI search and analysis on web using Desearch AI
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Model to use for the search: NOVA (default) or ORBIT. | NOVA |
| tools | No | Source ids sent to POST /desearch/ai/search. Use short ids such as 'web' and 'twitter'. Legacy labels such as 'Web Search' are accepted and rewritten to those ids. Example: ['web', 'twitter']. | |
| prompt | Yes | Question, example: 'What is the latest news on AI?' | |
| end_date | No | End of the date range in UTC (YYYY-MM-DDTHH:MM:SSZ). Use with start_date. | |
| start_date | No | Start of the date range in UTC (YYYY-MM-DDTHH:MM:SSZ). Use with end_date. | |
| date_filter | No | Deprecated relative window; prefer start_date/end_date. Example: 'PAST_WEEK' | |
| result_type | No | ONLY_LINKS returns links only; LINKS_WITH_FINAL_SUMMARY adds an AI summary. Link arrays are kept under whichever key the API uses, along with billing fields. ONLY_LINKS still depends on the API to include those links. | |
| exclude_domains | No | Drop Web Search results from these domains, example: ['pinterest.com'] | |
| include_domains | No | Restrict Web Search results to these domains, example: ['bbc.com', 'reuters.com'] |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered upstream. The description adds nothing behavioral beyond that — no mention of source coverage, latency, billing, or how results differ between models/sources. It essentially restates the annotation's open-world nature without new information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with zero padding or repetition — structurally clean. It avoids wasting tokens, though its brevity borders on under-specification rather than true conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 9-parameter, open-world search tool with no output schema, the description should at minimum hint at what comes back and how source/model selection shapes results. It supplies none of that, leaving the agent reliant entirely on the schema to understand a fairly complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all nine parameters (model, tools, date filters, result_type, domain filters) are already documented in the schema with defaults, enums, and examples. The description adds no parameter meaning whatsoever, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
"AI search and analysis on web using Desearch AI" gives a verb (search/analyze) and a resource (web), so the general purpose is inferable. But against siblings like web-search, x-search, and extract, it offers no distinguishing scope — it does not say what makes this an "AI" search versus the plain web-search tool. The purpose is vague enough that an agent couldn't confidently route between them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use guidance, no when-not-to-use, and no named alternative. With 14 siblings including web-search and x-search, an agent has no signal for choosing this tool over them. The description is purely a label, not usage instruction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extractExtract Page ContentARead-onlyInspect
Extract a public URL and return its content as plain text or HTML using Desearch. Preferred over web-crawl for new integrations.
| Name | Required | Description | Default |
|---|---|---|---|
| js | No | Render JavaScript before reading the page. | |
| url | Yes | Public URL to read, example: 'https://desearch.ai' | |
| wait | No | Post-load wait in milliseconds when JavaScript rendering is enabled. | |
| format | No | Content format to return: 'html' or 'text'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered structurally. The description adds one genuinely useful constraint beyond that — the URL must be public — plus the JS-rendering capability, but says nothing about rate limits, timeouts, content-size truncation, or failure behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core action and back-loaded with the sibling routing hint. No filler or redundant restatement of the title.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a four-parameter read tool with full schema coverage and annotations, the description covers purpose, output format, and alternative-tool routing. No output schema exists, but the return shape (text or HTML) is stated; only edge-case behavior like truncation or error handling is unaddressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents url, js, wait, and format. The description only echoes the format options ('plain text or HTML') and adds no syntax, defaults, or interaction details (e.g., that 'wait' only applies when 'js' is true) beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (extract) and resource (a public URL's content), and names the return formats (plain text or HTML). It also explicitly distinguishes itself from the sibling web-crawl, so an agent can choose between them without opening a schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The sentence 'Preferred over web-crawl for new integrations' names the alternative and the condition that selects this tool, which is exactly the kind of routing guidance an agent needs. It stops short of stating when NOT to use it (e.g., for non-public or authenticated pages beyond the implicit 'public URL' constraint).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
web-crawlCrawl Web Page (Legacy)ARead-onlyInspect
Crawl a public URL and return its content as plain text or HTML on the legacy Desearch /web/crawl route. The SDK marks webCrawl deprecated in favor of extract; this tool stays for parity with that route. Prefer extract for new integrations.
| Name | Required | Description | Default |
|---|---|---|---|
| js | No | Render JavaScript before reading the page. | |
| url | Yes | Public URL to read, example: 'https://desearch.ai' | |
| wait | No | Post-load wait in milliseconds when JavaScript rendering is enabled. | |
| format | No | Content format to return: 'html' or 'text'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds genuinely useful lifecycle context the annotations don't carry: deprecation status and legacy-route parity. It says nothing about auth needs, rate limits, or size/page limits, so with annotations carrying safety it lands at a solid 3.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, front-loaded with the core action and output. The 'legacy' concept is stated twice ('legacy Desearch /web/crawl route' and 'stays for parity with that route'), a minor redundancy that keeps it just short of a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description does cover the return shape (plain text or HTML) and the deprecation/alternative story, which is what an agent needs to choose and call it. Missing only operational details like payload size limits or JS-rendering caveats for a read-only, open-world crawl tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (js, url, wait, format are all documented in-schema with an enum for format). The description's mention of 'plain text or HTML' only echoes the format enum values, adding no syntax or behavioral detail beyond the schema. Baseline 3 applies when the schema does all the parameter work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource (crawl a public URL) and the exact output shapes (plain text or HTML), plus the underlying route (/web/crawl). It also distinguishes itself from the sibling 'extract' by naming it, so an agent can route without opening either schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Names the alternative tool explicitly ('Prefer extract for new integrations') and gives the condition that selects it (new vs. legacy integrations), plus the reason this tool still exists (parity with the legacy route). Nothing about when to pick this versus extract is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
web-links-searchWeb Links SearchBRead-onlyInspect
Search the web for links using Desearch. Only the web source is accepted.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Results to return per source. Min 10. Max 200. | |
| tools | No | Sources to search. Only 'web' is accepted; other ids are rejected before the API call. 'Web Search' is accepted and rewritten to 'web'. Defaults to ['web']. | |
| prompt | Yes | Search query prompt, example: 'open source browser automation tools' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the non-obvious behavioral fact that non-'web' source ids are rejected, but says nothing about result format, pagination, or latency/rate behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with the tool's action front-loaded and the source restriction immediately following. No filler beyond the minor branding mention of 'Desearch'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only search tool with rich annotations and a fully documented schema, this is adequate but thin. With no output schema, the description could have sketched what a result looks like, and it offers no context on how it differs from the many sibling search tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the schema documenting count bounds, the tools enum/default, and a prompt example, so the baseline is 3. The description adds nothing beyond the schema for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('search the web for links') plus the backend (Desearch), which is enough to identify it as a general web link search. It does not explicitly name the sibling it contrasts with (e.g. x-links-search or web-search), so an agent must infer differentiation from the namespace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The constraint 'Only the web source is accepted' implicitly tells the agent not to use this for X/Twitter link search, which is useful negative guidance. However, it never states when to prefer this over siblings like web-search, ai-search, or web-crawl, so selection guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
web-searchWeb SearchBRead-onlyInspect
SERP-style web search using Desearch. Returns ranked titles, links, and snippets.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query, example: 'latest news on AI' | |
| start | No | How many results to skip for pagination (0, 10, 20, ...). Omit for the first page. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety and open-world profile is covered structurally. The description adds useful return-shape context ('ranked titles, links, and snippets') that annotations do not convey, but says nothing about rate limits, result caps, or pagination behavior beyond what the schema hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact sentences, zero filler, with the core purpose front-loaded before the return-format detail. Nothing is padded or redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter, annotated, read-only search tool the description covers what it does and what it returns; the absence of an output schema makes the return-shape sentence valuable. It stops short of routing guidance relative to the many search siblings, which is the one real completeness gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and both parameters are documented there, including the pagination semantics of 'start', so the description adds no parameter-level meaning. Baseline 3 is appropriate when the schema carries the full burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('SERP-style web search') plus the backend ('Desearch') and the returned artifact (ranked titles, links, snippets). However it never distinguishes itself from siblings like ai-search, web-links-search, or extract, so an agent cannot tell which search entry point to choose without inferring.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance at all. With three closely related siblings (ai-search, web-links-search, x-search) the description gives no condition or exclusion that would route an agent to this tool over an alternative; the only hint is the implicit 'general web query' framing of 'SERP-style'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-links-searchX Links SearchBRead-onlyInspect
AI search for X (Twitter) post links using Desearch. Returns links from posts that match the prompt.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Results to return. Min 10. Max 200. | |
| prompt | Yes | Search query prompt, example: 'Bittensor subnet updates' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and destructiveHint=false, so safety is covered. The description adds that results come from an AI/Desearch pipeline and are links only, which is useful context, but says nothing about rate limits, result freshness, or what happens when no matches are found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, purpose front-loaded, with no filler. The second sentence is mildly redundant with the first ('search for post links' vs 'returns links from posts') but does clarify the return shape, which matters because there is no output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description usefully states that links are returned, and annotations carry the safety profile. However, for a tool sitting among five-plus overlapping search siblings, it lacks the differentiating detail an agent needs to route to it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with only two parameters, and the schema already documents prompt and count (including min/max bounds). The description adds no syntax, format, or prompt-engineering guidance beyond what the schema provides, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb (search) plus resource (X/Twitter post links) and the backing engine (Desearch), so an agent knows this returns links rather than posts. It implicitly separates itself from web-links-search by scoping to X, but never names or contrasts the many sibling search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no when-to-use guidance and no alternatives. Siblings like x-search, ai-search, and web-links-search overlap heavily, and nothing here explains which one an agent should pick for link discovery versus post retrieval.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-post-by-idGet X Post by IDBRead-onlyInspect
Fetch a single X (Twitter) post by its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The unique ID of the post, example: '1234567890' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds nothing beyond that: no auth requirements, no rate-limit note, no behavior for missing/invalid IDs or protected posts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One front-loaded sentence with zero filler; the resource and lookup key come first. Nothing is wasted and nothing is buried.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with no output schema and full annotation coverage, the definition is essentially sufficient to invoke correctly. It could go further on error/missing-post behavior, but nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single 'id' parameter is documented with an example in the schema itself. The description adds no format or constraint detail beyond what the schema already provides, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Fetch a single X post') plus the lookup key ('by its ID'), which implicitly separates it from x-posts-by-urls and x-posts-by-user. It never names a sibling or explicit boundary, so it falls short of the 5 tier.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance at all. With a crowded sibling set (x-posts-by-urls, x-posts-by-user, x-search, x-post-replies), the description should say when ID lookup is preferable, but it leaves the agent to infer everything.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-post-repliesGet X Post RepliesBRead-onlyInspect
Fetch replies to an X (Twitter) post, with an optional keyword query.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of posts to retrieve (1-100). | |
| query | No | Advanced search query to filter replies. | |
| post_id | Yes | The ID of the post to fetch replies for. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety and reach profile is covered. The description adds essentially nothing beyond that: no pagination behavior, no ordering, no rate-limit or result-cap context, and no note that count caps at 100.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with zero filler. The core action leads and the optional modifier trails it. Nothing can be trimmed without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with no output schema and full schema coverage, the description is barely sufficient. It leaves open the practical questions an agent faces: how many replies come back by default, whether results are paginated or ordered, and how the keyword query interacts with the fetched set.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents post_id, count (1-100), and the advanced query string. The description only restates the query parameter and adds no format, syntax, or default value detail, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Fetch replies to an X (Twitter) post.' That is unambiguous on its own. However, it does not distinguish this tool from close siblings such as x-user-replies (replies authored by a user) or x-search, so an agent must infer the boundary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use guidance, no prerequisites, and no mention of alternatives. The phrase 'with an optional keyword query' hints at filtering but never says when keyword filtering is preferable to a plain fetch or to using x-search for reply discovery.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-post-retweetersList X Post RetweetersARead-onlyInspect
List users who retweeted an X (Twitter) post. Pass cursor to page through more users.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The ID of the post to get retweeters for. | |
| cursor | No | Cursor for pagination from a previous response. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the pagination/cursor behavior, but says nothing about auth requirements, rate limits, or result completeness for a public X endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, zero filler, and the core action is front-loaded ahead of the paging hint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A simple two-parameter read tool; annotations carry the safety profile and the schema documents both params. There is no output schema, so the return shape is not explained, but nothing essential for a correct call is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and both parameters are fully documented in the schema, so the baseline is 3. The description restates cursor's purpose (paging) without adding syntax or format detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'List users who retweeted an X (Twitter) post.' The resource is precise enough to separate it from siblings like x-post-replies or x-posts-by-user, though no sibling is named explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'Pass cursor to page through more users' gives operational guidance for the pagination parameter, but there is no statement of when to use this tool versus the other X-post tools (e.g., replies, by-id). Usage is implied by the resource name rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-posts-by-urlsGet X Posts by URLsBRead-onlyInspect
Fetch full X (Twitter) posts for a list of post URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | Post URLs to fetch, example: ['https://x.com/user/status/123'] |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds essentially nothing beyond that — no batch size limits, rate-limit notes, behavior on invalid or deleted URLs, or partial-failure handling, which matter for a batch fetch against an open-world source.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler; the verb and resource come first. Nothing in the sentence is redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read tool with full schema coverage and safety annotations, the description is minimally sufficient. It is missing the operational context that would make a batch external fetch fully usable, such as batch limits or per-URL failure behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and there is only one parameter, so the schema carries the semantics (array of URL strings, minItems 1, with an example). The description only restates 'a list of post URLs' without adding format constraints or limits, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Fetch') and resource ('full X (Twitter) posts') scoped to a list of post URLs, which is specific enough to understand the operation. However, it does not distinguish itself from the closely related sibling x-post-by-id, which an agent might reasonably choose for the same intent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this bulk-by-URL tool versus x-post-by-id, x-user-posts, or x-search. The description also omits any prerequisites or conditions such as URL validity requirements or what happens with mixed/broken URLs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-posts-by-userSearch X Posts by UserBRead-onlyInspect
Search X (Twitter) posts by a specific user, with an optional keyword query.
| Name | Required | Description | Default |
|---|---|---|---|
| user | Yes | User to search for, example: 'elonmusk' | |
| count | No | Number of posts to retrieve (1-100). | |
| query | No | Advanced search query to filter this user's posts. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds nothing behavioral beyond that — no mention of rate limits, pagination, result ordering, or what an empty result means — making it essentially redundant with the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single tight sentence with no filler, and the core action is front-loaded. It is arguably too terse for a tool with a confusable sibling, but there is no wasted language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter read tool with full schema coverage and annotations, the description is minimally sufficient to call the tool correctly. It falls short on sibling disambiguation (x-user-posts) and any behavioral context about result volume or ordering.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all three parameters (user, count, query) are documented in the schema itself. The description restates the optional keyword query but adds no syntax, format, or default details beyond the schema, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource (search X posts) scoped to a user, plus an optional keyword filter. It is clear what the tool does, but it offers no differentiation from the very similar sibling x-user-posts, which an agent could easily confuse it with.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'with an optional keyword query' implies one usage pattern (keyword-filtered user timelines), but there is no explicit when-to-use guidance, no prerequisites, and no naming of alternatives such as x-search or x-user-posts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-searchX SearchBRead-onlyInspect
Search X (Twitter) using Desearch AI. Optional filters narrow by user, date, language, verification, media, and engagement. Sort stays Top.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language code, example: 'en', 'es', 'fr' | |
| user | No | User to search for, example: 'elonmusk' | |
| count | No | Number of search results to return (default: 20), max is 100 | |
| query | Yes | Twitter advanced search query, example: 'from:elonmusk since:2023-01-01 min_replies:10' | |
| end_date | No | End date in UTC (YYYY-MM-DD). Use with start_date. | |
| is_image | No | Include only posts with images. | |
| is_quote | No | Include only posts that are quotes. | |
| is_video | No | Include only posts with video. | |
| verified | No | Filter for verified users. | |
| min_likes | No | Minimum number of likes. | |
| start_date | No | Start date in UTC (YYYY-MM-DD). Use with end_date. | |
| min_replies | No | Minimum number of replies. | |
| min_retweets | No | Minimum number of retweets. | |
| blue_verified | No | Filter for blue-checkmark verified users. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds one genuinely useful behavioral fact beyond the schema — 'Sort stays Top' — meaning ordering cannot be changed, but it says nothing about result volume, rate limits, or the cost of the AI-backed search.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core action and followed by the qualifier about optional filters. There is minimal waste, though the 'using Desearch AI' branding adds little operational value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 14 parameters and no output schema, the description is thin: it does not describe the return shape (posts? fields?), pagination, or the cost/latency of an AI-backed search. The 100%-covered schema compensates for parameter documentation, making this merely adequate rather than inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, including the format example for 'query' and the min_* engagement filters, so the schema does the heavy lifting. The description only recaps filter categories (user, date, language, verification, media, engagement), adding no syntax or constraint detail beyond what parameters already document.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Search X (Twitter)') and names the underlying engine (Desearch AI), so the agent knows this is a general keyword/query search. It does not, however, explicitly distinguish itself from close siblings like x-links-search, x-posts-by-user, or web-search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by noting that filters are optional and narrow results, but it never states when to pick this tool over siblings such as x-user-posts or x-links-search, nor any prerequisites or exclusions. Guidance is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-trendsGet X TrendsBRead-onlyInspect
Retrieve trending topics on X (Twitter) for a location by its WOEID using Desearch.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of trends to return (30-100). | |
| woeid | Yes | WOEID of the location, example: 23424977 for the United States. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety and scope profile is covered. The description adds only that results come from Desearch, and says nothing about rate limits, freshness of trends, or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with zero filler, front-loading the action and resource before the input mechanism. Nothing is redundant or padded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only two-parameter tool with no output schema and full schema coverage, the description is nearly complete. It could note what a trend entry looks like or whether count defaults, but nothing critical to correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both woeid and count are documented in the schema with ranges and an example. The description adds no syntax or format detail beyond repeating the WOEID requirement, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (retrieve) and resource (trending topics on X/Twitter), plus the scoping mechanism (location via WOEID). It does not explicitly name a sibling, but no sibling covers trends, so it is implicitly distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no statement of when to use this tool versus alternatives, no prerequisites, and no exclusions; the only added detail is the data source (Desearch). An agent must infer usage entirely from the name and the WOEID requirement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-user-postsGet X User TimelineCRead-onlyInspect
Retrieve a user's X (Twitter) timeline posts by username. Pass cursor to page through more posts.
| Name | Required | Description | Default |
|---|---|---|---|
| cursor | No | Cursor for pagination from a previous response. | |
| username | Yes | Username to fetch posts for, example: 'elonmusk' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered without the description. The description adds nothing beyond that — no notes on rate limits, auth requirements, result ordering, or timeline scope (e.g., replies/retweets included) — so its behavioral contribution is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core action and free of filler. The second sentence is somewhat redundant with the schema's cursor description, so it doesn't fully earn its place, but overall sizing is appropriate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read tool with full schema coverage and a complete read-only annotation set, the description is adequate. It omits what the returned post objects contain (no output schema exists) and, more importantly, how this differs from the sibling x-posts-by-user.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (username, cursor) are already documented in the schema, giving a baseline of 3. The description's cursor note restates pagination behavior rather than adding format or semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource ('Retrieve a user's X (Twitter) timeline posts by username'), which is clearer than a bare name restatement. However, it offers no differentiation from the near-identical sibling x-posts-by-user (or x-search/x-user-replies), leaving the agent unable to tell which to pick without opening schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use or when-not-to-use guidance and no named alternative. The only operational note, 'Pass cursor to page through more posts,' is parameter mechanics rather than selection guidance, so the agent gets no help choosing between this and x-posts-by-user.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
x-user-repliesGet X User RepliesBRead-onlyInspect
Fetch posts and replies by an X (Twitter) user, with an optional keyword query.
| Name | Required | Description | Default |
|---|---|---|---|
| user | Yes | Username of the user to search for, example: 'elonmusk' | |
| count | No | Number of posts to retrieve (1-100). | |
| query | No | Advanced search query to filter this user's posts and replies. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds the useful behavioral detail that both posts and replies are returned, but says nothing about pagination, rate limits, or result ordering.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler; the primary action and the optional qualifier are both stated immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only, 3-parameter tool with no output schema this is minimally adequate, but it leaves the overlap with x-user-posts and x-post-replies unresolved and gives no hint about result volume or pagination behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all three parameters are already documented. The description only restates the optional keyword query, adding no format, syntax, or default semantics beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (Fetch) and resource (posts and replies by an X user), so the agent knows the operation. However, it does not differentiate itself from close siblings like x-user-posts, x-post-replies, or x-search, and the phrase 'posts and replies' blurs the boundary with x-user-posts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance is given. The mention of an 'optional keyword query' implies a filtered-search use case, but the description never says when to prefer this tool over x-user-posts, x-post-replies, or x-search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.3- Changed
ai-search1 field changed- changed
Input schema / properties / model / descriptionPrevious value: -"Model to use for the search, example: 'NOVA', Nova is 10s model, Orbit is 30s model"New value: +"Model to use for the search: NOVA (default) or ORBIT."
15 tool updates
v0.1.2- First observed
ai-search - First observed
extract - First observed
web-crawl - First observed
web-links-search - First observed
web-search - First observed
x-links-search - First observed
x-post-by-id - First observed
x-post-replies - First observed
x-post-retweeters - First observed
x-posts-by-urls - First observed
x-posts-by-user - First observed
x-search - First observed
x-trends - First observed
x-user-posts - First observed
x-user-replies
TDQS
Scored across 15 tools
Most tools target distinct resource+action pairs (e.g., x-post-by-id vs x-posts-by-urls), and descriptions clarify differences. However, x-posts-by-user and x-user-posts are easily confused, and x-search vs x-links-search require careful reading to distinguish. Overall mostly distinct but with minor overlap.
Kebab-case is used throughout with clear prefixes (x- for X/Twitter, web- for web, ai- for AI). Minor inconsistencies exist in singular/plural (x-post-by-id vs x-posts-by-urls) and phrasing (x-posts-by-user vs x-user-posts), but the pattern remains predictable and readable.
15 tools is well-scoped for a search/crawl API covering multiple sources and endpoints. Each tool maps to a specific Desearch capability, and the deprecated web-crawl is justified for route parity.
Covers web search, AI search, link search, content extraction/crawl, X post retrieval by ID/URLs/user, replies, retweeters, and trends. Minor gaps include no direct X user profile lookup or hashtag search, but core workflows are well-covered.
Maintenance
Related MCP Connectors
X (Twitter) search, profiles and global trends, plus YouTube search, video stats and comments.
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